Brief Bio: I received a bachelor's degree in Physics from St. Stephen's College, University of Delhi in 1997 and another one in Computation from the University of Oxford in 2000 on a Rhodes Scholarship. I then stayed on at Oxford on a University Scholarship and obtained a DPhil in Engineering in 2004. Before joining Microsoft Research I was a Post-Doctoral Fellow at MSRI Berkeley. I have been an Adjunct Professor at the Indian Institute of Technology (IIT) Delhi in the Computer Science and Engineering Department since 2009 and jointly in the School of Information Technology since 2011. My research interests lie in the areas of machine learning, computational advertising and computer vision. I have served as an Area Chair for machine learning and computer vision conferences such as NIPS and ICCV.

Research

I am interested in the following research areas

• Machine Learning - Multiple Kernel Learning, Multi-Label Classification, Support Vector Machines, Supervised Learning.
• Computer Vision - Image Search, Object Recognition, Text Recognition, Texture Classification.
• Computational advertising - Bid Phrase Suggestion, Contextual Matching.

If you would like to apply for an internship at Microsoft Research India then please e-mail me directly. This is better than applying online as it'll ensure that I go through your application. However, since I get a lot of requests, I might not be able to respond to each of your e-mails in person. Internships are open throughout the year and typically last between 3 to 6 months (though this is quite flexible).

If you are interested in computer vision or machine learning research supervision at IIT Delhi then please come and meet me (Room 312, Bharti Building) or e-mail me directly. IIT offers PhD Studentships in collaboration with MSR India. Please look at the CSE Department web pages for more details and other funding opportunities.

I am looking for a Research Scientist to work with me at IIT Delhi on computer vision and machine learning. The position is for two years and is funded by the Department of Science and Technology, Government of India. Candidates must have an excellent BTech/BE degree in Computer Science or related disciplines. An MS/PhD in Computer Vision or Machine Learning with publications in top tier conferences is preferblue. The project will require visits to the Hebrew University of Jerusalem.

Conferences, Workshops and Links

• ICCV 2013 (Area Chair)
• Machine Learning Summit 2013 - Learning With Millions of Categories
• WebVision at ECCV 2012
• ICVGIP 2012 (Area Chair)
• The Mysore Park Workshop on Computer Vision
• NIPS 2011 (Area Chair)
• ICVGIP 2010 (Area Chair)
• The 3rd MSRI Computer Vision & Graphics Shindig
• The 2010 Winter School on Machine Learning and Computer Vision
• Teaching at IIT Delhi

Publications

• R. Agrawal, A. Gupta, Y. Prabhu and M. Varma. Multi-label learning with millions of labels: Recommending advertiser bid phrases for web pages. In Proceedings of the International World Wide Web Conference, Rio de Janeiro, Brazil, May 2013.
  Bibtex source | Abstract | Download in pdf format | Slides



• A. Jain, S. V. N. Vishwanathan and M. Varma. SPG-GMKL: Generalized multiple kernel learning with a million kernels. In Proceedings of the ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Beijing, China, August 2012.
  Bibtex source | Abstract | Download in pdf format | Code



• B. Hariharan, S. V. N. Vishwanathan and M. Varma. Efficient max-margin multi-label classification with applications to zero-shot learning. Machine Learning Journal, , 88(1):127--155, 2012.
  Bibtex source | Abstract | Download in pdf format | Code



• V. Jain and M. Varma. Learning to re-rank: Query-dependent image re-ranking using click data. In Proceedings of the International World Wide Web Conference, Hyderabad, India, March 2011.
  Bibtex source | Abstract | Download in pdf format | Slides



• S. V. N. Vishwanathan, Z. Sun, N. Theera-Ampornpunt and M. Varma. Multiple kernel learning and the SMO algorithm. In Advances in Neural Information Processing Systems, Vancouver, B. C., Canada, December 2010.
  Bibtex source | Abstract | Download in pdf format | Code | Spotlight



• B. Hariharan, L. Zelnik-Manor, S. V. N. Vishwanathan and M. Varma. Large scale max-margin multi-label classification with priors. In Proceedings of the International Conference on Machine Learning, Haifa, Israel, June 2010.
  Bibtex source | Abstract | Download in pdf format | Code



• M. Varma and A. Zisserman. A statistical approach to material classification using image patch exemplars. IEEE Transactions on Pattern Analysis and Machine Intelligence , 31(11):2032--2047, November 2009.
  Bibtex source | Abstract | Download in pdf format



• A. Vedaldi, V. Gulshan, M. Varma and A. Zisserman. Multiple kernels for object detection. In Proceedings of the International Conference on Computer Vision, Kyoto, Japan, September 2009.
  Bibtex source | Abstract | Download in pdf format | Code



• M. Varma and B. R. Babu. More generality in efficient multiple kernel learning. In Proceedings of the International Conference on Machine Learning, Montreal, Canada, pages 1065--1072, June 2009.
  Bibtex source | Abstract | Download in pdf format | Code



• T. E. de Campos, B. R. Babu and M. Varma. Character recognition in natural images. In Proceedings of the International Conference on Computer Vision Theory and Applications, Lisbon, Portugal, February 2009.
  Bibtex source | Abstract | Download in pdf format | Download English and Kannada datasets



• M. Varma and D. Ray. Learning the discriminative power-invariance trade-off. In Proceedings of the IEEE International Conference on Computer Vision, Rio de Janeiro, Brazil, October 2007.
  Bibtex source | Abstract | Download in pdf format | www | Code | Errata
  Please see the errata regarding the Caltech experiments



• M. Varma and R. Garg. Locally invariant fractal features for statistical texture classification. In Proceedings of the IEEE International Conference on Computer Vision, Rio de Janeiro, Brazil, October 2007.
  Bibtex source | Abstract | Download in pdf format



• N. Adabala and M. Varma and K. Toyama. Computer aided generation of stylized maps. Computer Animation and Virtual Worlds, 18(2):133--140, May 2007.
  Bibtex source | Abstract | Download in pdf format



• M. Varma and A. Zisserman. A statistical approach to texture classification from single images. International Journal of Computer Vision: Special Issue on Texture Analysis and Synthesis, 62(1--2):61--81, April 2005.
  Bibtex source | Abstract | Download in pdf format



• M. Varma and A. Zisserman. Unifying statistical texture classification frameworks. Image and Vision Computing, 22(14):1175--1183, December 2004.
  Bibtex source | Abstract | Download in pdf format



• M. Varma. Statistical Approaches To Texture Classification. DPhil Thesis, University of Oxford, October 2004.
  Bibtex source | Abstract | Download in pdf format (~18 Mb)



• M. Varma and A. Zisserman. Estimating illumination direction from textublue images. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Washington, DC, volume 1, pages 179--186, June 2004.
  Bibtex source | Abstract | Download in pdf format



• M. Varma and A. Zisserman. Texture classification: Are filter banks necessary? In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Madison, Wisconsin, volume 2, pages 691--698, June 2003.
  Bibtex source | Abstract | Download in pdf format



• M. Varma and A. Zisserman. Statistical approaches to material classification. In Proceedings of the Indian Conference on Computer Vision, Graphics and Image Processing, Ahmedabad, India, pages 167--172, December 2002.
  Bibtex source | Abstract | Download in pdf format



• M. Varma and A. Zisserman. Classifying materials from images: to cluster or not to cluster? In Proceedings of the 2nd International Workshop on Texture Analysis and Synthesis, Copenhagen, Denmark, pages 139--144, June 2002.
  Bibtex source | Abstract



• M. Varma and A. Zisserman. Classifying images of materials: Achieving viewpoint and illumination independence. In Proceedings of the 7th European Conference on Computer Vision, Copenhagen, Denmark, volume 3, pages 255--271. Springer-Verlag, May 2002.
  Bibtex source | Abstract | Download in pdf format



• M. Varma and V. S. Varma. Computer simulation of evolution. In Proceedings of the GIREP-ICPE International Conference, Ljubljana, Slovenia, pages 138--150, August 1996.
  Bibtex source